U.S. patent number 9,535,068 [Application Number 13/884,702] was granted by the patent office on 2017-01-03 for oral cancer point of care diagnostics.
This patent grant is currently assigned to William Marsh Rice University. The grantee listed for this patent is Nicolaos Christodoulides, Pierre N. Floriano, John T. McDevitt, Craig Murdoch, Spencer Redding, Paul Speight, Martin Thornhill, Nadarajah Vigneswaran. Invention is credited to Nicolaos Christodoulides, Pierre N. Floriano, John T. McDevitt, Craig Murdoch, Spencer Redding, Paul Speight, Martin Thornhill, Nadarajah Vigneswaran.
United States Patent |
9,535,068 |
McDevitt , et al. |
January 3, 2017 |
Oral cancer point of care diagnostics
Abstract
A point of care diagnostic test, device and disposables for
determining a patient risk for oral cancer in the same visit that a
sample is collected.
Inventors: |
McDevitt; John T. (Houston,
TX), Christodoulides; Nicolaos (Houston, TX), Floriano;
Pierre N. (Missouri City, TX), Thornhill; Martin
(Sheffield, GB), Redding; Spencer (San Antonio,
TX), Vigneswaran; Nadarajah (Houston, TX), Murdoch;
Craig (Sheffield, GB), Speight; Paul (Sheffield,
GB) |
Applicant: |
Name |
City |
State |
Country |
Type |
McDevitt; John T.
Christodoulides; Nicolaos
Floriano; Pierre N.
Thornhill; Martin
Redding; Spencer
Vigneswaran; Nadarajah
Murdoch; Craig
Speight; Paul |
Houston
Houston
Missouri City
Sheffield
San Antonio
Houston
Sheffield
Sheffield |
TX
TX
TX
N/A
TX
TX
N/A
N/A |
US
US
US
GB
US
US
GB
GB |
|
|
Assignee: |
William Marsh Rice University
(Houston, TX)
|
Family
ID: |
46051596 |
Appl.
No.: |
13/884,702 |
Filed: |
November 11, 2011 |
PCT
Filed: |
November 11, 2011 |
PCT No.: |
PCT/US2011/060453 |
371(c)(1),(2),(4) Date: |
July 01, 2013 |
PCT
Pub. No.: |
WO2012/065117 |
PCT
Pub. Date: |
May 18, 2012 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20130295580 A1 |
Nov 7, 2013 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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61413107 |
Nov 12, 2010 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N
33/57407 (20130101); G01N 2333/71 (20130101); G01N
2333/47 (20130101); G01N 2333/70596 (20130101); G01N
2333/4703 (20130101) |
Current International
Class: |
G01N
33/53 (20060101); G01N 33/574 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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2004009840 |
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Jan 2004 |
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WO |
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2005083423 |
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Sep 2005 |
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WO |
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2005085796 |
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Sep 2005 |
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WO |
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2007002480 |
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Jan 2007 |
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WO |
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Other References
Torres-Rendon et al. "Expression of MCM2, geminin and Ki67 in
normal oral mucosa, oral epithelial dysplasias and their
corresponding squamous-cell carcinomas", British Journal of Cancer,
2009, 100, 1128-1134. cited by examiner .
Weigum, S. E.; Floriano, P. N.; Christodoulides, N.; McDevitt, J.
T. ""Cell-based sensor for analysis of EGFR biomarker expression in
oral cancer, Lab on a Chip 2007, 7, 995-1003. cited by applicant
.
Weigum, S.E. et al, "Nano-Bio-Chip Sensor Platform for Examination
of Oral Exfoliative Cytology," Cancer Prevention Research 2010, 3,
518-528. cited by applicant.
|
Primary Examiner: Counts; Gary W
Attorney, Agent or Firm: Boulware & Valoir
Government Interests
FEDERALLY SPONSORED RESEARCH STATEMENT
This invention was made with government support under Grant No:
RC2-DE20785, awarded by the NIH. The government has certain rights
in the invention.
Parent Case Text
PRIOR RELATED APPLICATIONS
This application is a National Phase filing under 35 U.S.C.
.sctn.371 of International Application PCT/US11/60453, filed on
Nov. 11, 2011, which claims priority to U.S. Provisional
Application 61/413,107, filed Nov. 12, 2010. Both applications are
incorporated herein by reference in their entirety.
Claims
What is claimed is:
1. A method of point of care testing to distinguishing oral cancer
from dysplasia and benign lesions, said method comprising: a)
collecting an oral sample from a patient during a patient visit
using a rotating brush; b) applying said sample to a portable
device comprising microfluidics, a power source, display means, a
removable and disposable chip comprising reagents for detecting
DNA, cytoplasm, and at least three biomarkers selected from the
group consisting of AVB6, EGFR, Ki67, Geminin, MCM2, Beta Catenin,
and EMMPRIN; c) measuring, by using said portable device,
nuclear/cytoplasm ratio, cell roundness, cell aspect ratio, and
cell shape, and said at least three biomarkers in said sample; d)
computing, by using said portable device, the risk of oral squamous
cell carcinoma (OSCC score) based on said measurements and the
formula: OSCC
score=a.sub.0+a.sub.1.times.P.sub.1+a.sub.2.times.P.sub.2+ . . .
+a.sub.n.times.P.sub.n wherein a.sub.1.fwdarw.n are weighing
coefficients, and P.sub.1.fwdarw.n are parameters selected from
said measurements in step c) and said detecting results from step
b), and wherein risk of oral cancer is directly proportional to
nuclear/cytoplasmic area ratio, cell roundness, EGFR, KI67,
Geminin, AVB6, MCM2, beta catenin and EMMPRIN and inversely
correlated with cell aspect ratio and the risk of benign lesions is
the reverse; and e) communicating, by using said portable device,
said risk to the patient in the same patient visit as said
collecting step a) to distinguish oral cancer from dysplasia and
benign lesions.
2. The method of claim 1, wherein said testing has at least 90%
specificity and 90% sensitivity.
3. The method of claim 1, wherein said testing has at least 93%
specificity and 97% sensitivity.
Description
REFERENCE TO MICROFICHE APPENDIX
Not applicable.
FIELD OF THE INVENTION
This invention generally relates to methods, devices, disposables
and systems for point of care diagnosis of oral cancer, and is an
improvement on US2008038738, incorporated in its entirety by
reference.
BACKGROUND OF THE INVENTION
All squamous cell carcinoma lesions are thought to begin via the
repeated, uncontrolled division of cancer stem cells of epithelial
lineage or characteristics. Accumulation of these cancer cells
cause a microscopic focus of abnormal cells that are, at least
initially, locally confined within the specific tissue in which the
progenitor cell resided. This condition is called squamous cell
carcinoma in situ, and it is diagnosed when the tumor has not yet
penetrated the basement membrane or other delimiting structure to
invade adjacent tissues. Once the lesion has grown and progressed
to the point where it has breached, penetrated, and infiltrated
adjacent structures, it is referred to as "invasive" squamous cell
carcinoma. Once a carcinoma becomes invasive, it is able to spread
to other organs and cause a metastasis or secondary tumor to
form.
Oral cancer is a subtype of head and neck cancer and is any
cancerous tissue growth located in the oral cavity. It may arise as
a primary lesion originating in any of the oral tissues, by
metastasis from a distant site of origin, or by extension from a
neighboring anatomic structure, such as the nasal cavity. Oral
cancers may originate in any of the tissues of the mouth, and may
be of varied histologic types: teratoma, adenocarcinoma derived
from a major or minor salivary gland, lymphoma from tonsillar or
other lymphoid tissue, or melanoma from the pigment-producing cells
of the oral mucosa. There are several types of oral cancers, but
around 90% are squamous cell carcinomas, originating in the tissues
that line the mouth and lips.
Oral squamous cell carcinoma (OSCC) is a global health problem
afflicting close to 300,000 people each year. Despite significant
advances in surgical procedures and treatment, the long-term
prognosis for patients with OSCC remains poor, with a 5-year
survival rate at approximately 50%, which is among the lowest for
all major cancers. High mortality associated with OSCC is often
attributed to advanced disease stage at diagnosis, underscoring the
need for new diagnostic methods targeting early tumor progression
and malignant transformations.
SUMMARY OF THE INVENTION
Our initial proof of concept work was described in Weigum, S. E. et
al., Nano-Bio-Chip Sensor Platform for Examination of Oral
Exfoliative Cytology, Cancer Prevention Research 2010, 3, 518-528,
expressly incorporated by reference. However, these initial
experiments were primitive, in that they did not employ a standard
disposable card, used bench top fluidics and examined only a single
biomarker. This invention has now been improved to use a disposable
card containing reagents, a commercially available analyser, and a
panel of biomarkers are analyzed, as described below.
We have developed a programmable bio-nano-chip that allows for the
analysis of cellular samples obtained from a minimally invasive
brush biopsy sample. This invention describes an improved panel of
biomarkers to cover early oral cancer detection and progression,
and the technology also has applications into potential rare cell
detection. The cell suspensions allow for the simultaneous
quantification of cell morphometric data and expression of
molecular biomarkers of malignant potential in an automated manner
using refined image analysis algorithms based on pattern
recognition techniques and advanced statistical methods. The device
has at least 90% specificity and 90% sensitivity, preferably at
least 92, 93, 94, 95, 96, or 97%.
The chip-based platform is adapted to include a panel of biomarkers
indicative of dysplasia as derived from cytomorphometric and
molecular data. As such the programmable bio-nano-chip will be
augmented with customized panels of the tumor markers alphaV beta6,
Epidermal Growth Factor Receptor (EGFR), Ki67, Geminin, Mini
Chromosome Maintenance protein (MCM2), Beta Catenin, and EMMPRIN
(CD147). Expression of those markers has already been shown to
correlate with increasing dysplasia and malignant change
(conversion to cancer).
To summarize the invention, the diagnostic is performed on a
portable device together with disposable biochips, that contains
various liquid and/or dried reagents. The analyzer device contains
microfluidics for sample and reagent flow, means for detecting
signals, usually light based signals, computing means for analyzing
collected data and usually means for inputting patient information
and displaying final results.
Generally speaking, the disposable lab cards contain a detection
window which has a membrane therein sized to capture cells. In
preferred embodiments, this membrane is exchangeable, e.g., with
membranes of differening size, or with arrays of antibodies, and
thus is contained inside a hinged door or lid or similar components
that serves to lock the exchangeable component into the card.
An inlet port is fluidly connected to the detection window, and
sample is applied and travels to the window where cells are trapped
by the membrane. The card preferably also contains regent chambers,
although simple cards have been tested without same, and the
analyser activates the reagent chamber, pushing wash fluid to the
detection window to wash away cell debris as needed. Next, a second
reagent chamber is activated, and travels past a dry pad or chamber
containing dry antibodies and stains, reconstitutes same and
carries these to the detection window, where the cells are stained
with nuclear, cytoplasmic and antibody stains. Optionally, these
reagents can be premixed with the second chamber fluid, but
stability of antibody components is improved in the dry form.
Preferably these dry pads are also exchangeable, e.g. via a hinged
lid. The excess reagents can then bewashed away, using wash from
the first chamber, and the remaining signals detected and analyzed.
Additional detection windows can be provided, depending on the
number of analytes to be analyzed and the spectral range of the
signals (and device capacity to distinguish same). Alternatively,
the cells can be serially stained, and then washed clean and
restrained.
These disposable lab cards are not detailed beyond this basic
description, but are described more fully in U.S. Ser. Nos.
61/484,492, filed May 10, 2011, and 61/558,165, filed Nov. 10,
2011, and each expressly incorporated by reference in its entirety
for all purposes.
The card shape, size and fluidics and placement of chambers or
blisters will of course vary according to the analyzer selected.
The analyzer can be any desk top analyzer, or a commercially
available brand, such as that by LABNOW.TM. (Austin Tex.) or Force
Diagnostics.TM. (Chicago, Ill. and Houston, Tex.). Other devices
and systems can be used and are e.g., described in WO2007002480,
WO2005083423, WO2004009840, WO2005085796 and US2009215072.
In preferred embodiments a suspension of cells is collected with a
rotating brush. Our research has indicated that collecting cells in
the way is sufficient to permeabilize the cells for our purposes,
but it is also possible to fix and permeabilize the whole cells in
the usual way. The cells can be collected on a membrane that allows
debris to pass through, but not whole cells. Alternatively, it is
also possible to enrich for a particular population of cells with
e.g., magnetic beads coupled, e.g., to a receptor or cell surface
proteins, such as an antibody for EGFR. This can be done in a
pre-chamber before reaching the detection window. Then when the
magnet is turned off, the enriched cancer cells can pass to the
image cytometer. Using this technique we have already been able to
detect a single cell in 10,000 and we expect that we can easily get
to 10.sup.6 and 10.sup.9 sensitivity when fully optimized.
The system then detects a variety of morphological and biological
markers, including for example, DAPI for DNA, and phalloidin for
F-actin. These two stains provide a great deal of information about
cell morphology, and for example, nuclear to cytoplasm size or
diameter ratios (important indicators that a cell is transforming)
and cell shape (cancer cells are rounder). Other parameters that
can be measured and used in the model include but are not limited
to:
Area (WCArea[red])--Area of Whole cell selection in square pixels
determined in red from Phalloidin stain.
Mean Intensity Value (WCMean[red], [green])--Average value within
the WC selection. This is the sum of the intensity values of all
the pixels in the selection divided by the number of pixels. [red]
has QA/QC value and [blue] has limited descriptive value, whereas
[green] is the most important for surface markers. For
intracellular markers, the NuMean[green] is most descriptive.
Standard Deviation (WCStdDev[red], [green])--Standard deviation of
the intensity values used to generate the mean intensity value.
[red] useful for Phalloidin, QA/QC and descriptive, [green] for
surface markers.
Modal Value (WCMode[red], [green])--Most frequently occurring value
within the selection. Corresponds to the highest peak in the
histogram. Similar to Mean in terms of value.
Min & Max Level (WCMin and WCMax[red], [green], [blue]--Minimum
and maximum intensity values within the selection. This parameter
has limited descriptive value, but may be used for quality
assurance (QA), quality control (QC).
Integrated Density (WCIntDen[red], [green], [blue])--Calculates and
displays "IntDen" (the product of Area and Mean Gray
Value)--Dependent values.
Median (WCMedian[red], [green])--The median value of the pixels in
the image or selection. This again is similar to Mean and Mode in
terms of utility.
Circ. (circularity): 4.pi.*area/perimeter.sup.2. A value of 1.0
indicates a perfect circle. As the value approaches 0.0, it
indicates an increasingly elongated shape. Values may not be valid
for very small particles.
AR (aspect ratio): diameters of major_axis/minor_axis.
Round (roundness): 4*area/(.pi.*major_axis.sup.2), or the inverse
of the aspect ratio.
Other parameters may include percentages of cells with one or more
parameters meeting certain criteria, or above a certain
cut-off.
Cells can also be stained with labeled antibodies for the various
cancer markers discussed herein. Generally, different biomarkers
should be labeled with different labels, so that they can be
distinguished. However, some overlap is allowable where the markers
are spatially distinguished in the cell, e.g., EGFR on the cell
surface and Ki67 in the nucleus. Alternatively, the chip can be
divided into two or three portions (or two chips used) and separate
groups of labels employed, or the chip can have multiple detection
windows or portions thereof having separate fluidics.
The following abbreviations are used herein:
TABLE-US-00001 Abbreviations Ab Antibody ABS Acrylonitrile
butadiene styrene AUC Area under the curve AVB6 or .alpha.V.beta.6
Alpha V beta 6, an integrin BM Biomarker DNA Deoxyribonucleic acid
EGFR Epidermal Growth Factor Receptor EMMPRIN Extracellular Matrix
Metalloproteinase Inducer, aka CD147 FITC Fluorescein
isothiocyanate HNSCC Head and neck squamous cell carcinomas IVD in
vitro diagnostic device Ki67 Antigen KI-67 also known as Ki-67 or
MKI67 is a protein that in humans is encoded by the MKI67 gene LOD
Limits of detection MAB Monoclonal Ab MCM2 Mini Chromosome
Maintenance protein 2 N/C ratio nuclear/cytoplasmic ratio NBC
Nano-bio-chip NPV or PV.sup.- Negative predictive value NSE
Neuron-specific enolase OSCC oral squamous cell carcinoma PBSA
Phosphate buffered saline with bovine serum albumin PML potentially
malignant lesions PNBC Programmable BNC PPV or PV.sup.+ positive
predictive value PV Predictive value RNA Ribonucleic acid ROC
Receiver operating characteristic. A graphical plot of the
sensitivity, or true positive rate, vs. false positive rate (1 -
specificity or 1 - true negative rate), for a binary classifier
system as its discrimination threshold is varied. The ROC can also
be represented equivalently by plotting the fraction of true
positives out of the positives (TPR = true positive rate) vs. the
fraction of false positives out of the negatives (FPR = false
positive rate). Also known as a Relative Operating Characteristic
curve, because it is a comparison of two operating characteristics
(TPR & FPR) as the criterion changes. ROI Region of interest
Wnt Proto-oncogene protein Wnt .beta.-catenin Beta Catenin is a
protein that in humans is encoded by the CTNNB1 gene
The word "morphometric" as used herein means the measurement of
such cellular shape or morphological characteristics as cell shape,
size, nuclear to cytoplasm ratio, membrane to volume ratio, and the
like.
The word "a" or "an" when used in conjunction with the term
"comprising" in the claims or the specification means one or more
than one, unless the context dictates otherwise.
The term "about" means the stated value plus or minus the margin of
error of measurement or plus or minus 10% if no method of
measurement is indicated.
The use of the term "or" in the claims is used to mean "and/or"
unless explicitly indicated to refer to alternatives only or if the
alternatives are mutually exclusive.
The terms "comprise", "have", "include" and "contain" (and their
variants) are open-ended linking verbs and allow the addition of
other elements when used in a claim.
The phrase "consisting of" is closed, and excludes all additional
elements.
The phrase "consisting essentially of" excludes additional material
elements, but allows the inclusions of non-material elements that
do not substantially change the nature of the invention.
DESCRIPTION OF FIGURES
FIG. 1A is a bio-nano-chip system that includes lab card, and
analyzer. The single marker or multi-marker oral cancer
bio-nano-chip is an in vitro diagnostic device (IVD) that includes
lab card, assay and analyzer, intended to simultaneously identify
and quantitate the level of expression of a panel of biomarkers for
dysplasia and cancer including alphaV beta6, Epidermal Growth
Factor Receptor (EGFR), Ki67, Geminin, Mini Chromosome Maintenance
protein (MCM2), Beta Catenin, and EMPPRIN (CD147), as well as
cytomorphometric parameters such as nuclear area, nuclear to
cytoplasm ratio, and other cell-based morphological characteristics
to yield a multi-marker signature using cells collected with a
minimally invasive brush biopsy approach. The small insets show
cells capture by the membrane, and cells with fluorescent
stain.
FIG. 1B shows an exemplary card in additional detail. The BNC assay
card is composed of a number of modular subassemblies, including
(1) multilayered microfluidics card, (if) bead support chip, (iii)
two fluid filled blister packs, and (iv) a sample input port. Solid
state pad-based reagents are added to the card after fabrication
via an access ports on the card's surface (v). Here, the modular
and programmable nature of the design allows the PBNC to be
reconfigured to accommodate new detection modalities without
changing the underlying microfluidic architecture of the LOC. The
card is designed to interface with a compact and portable analyzer
that integrates the mechanical, electrical, and optical components
necessary for analysis. Together the three components constitute a
compact field-deployable bead-based assay system capable of highly
multiplexed quantitative analysis of complex fluids such as serum
and saliva.
FIG. 1C shows a second generation card with improved microfluidics,
bubble traps, herringbone mixers, vents, and the like. A piping
diagram of the PBNC's microfluidic network shows the principle
microfluidic channels and features. The sample metering channel
features a port for sample input (1) configured with an inline
membrane filter, a bubble trap (ii), a metered sample loop (ii1),
and a sample overflow chamber (iv) leading to an external vent (v).
The right-hand fluid containing blister pack (vi) intersects the
sample loop to evacuate the metered portion of sample toward the
membrane housed in the detection window (vii). Air behind the array
is purged through a wetting vent (viii). The reagent preparation
channel links the left-hand containing blister (ix) to a
solid-state reagent storage chamber (x) followed by an inline
track-etch membrane filter (xi) and bubble trap (xii). Both the
sample metering channel and reagent preparation channel confluence
at the distal bubble trap, which forms a junction column with a
single output. The common channel features six staggered
herringbone mixer sets (xiil) configured asymmetrically on the top
and bottom channel substrate leading to the bead sensors. The drain
to the analysis chamber directs all flow to a large capacity
bilateral waste reservoir (xiv). The waste reservoir vents (xv) are
covered with selectively permeable vent membranes for secure waste
containment.
FIG. 2 Microphotographs obtained for various biomarker assays on
the programmable bio-nano-chip platform.
FIG. 3 Bar graph of the percentage of cells with intensity lying 2
standard deviations above the mean EGFR intensity for the 100%
MDACC cells (left). Average measured nuclear area as a function of
increasing concentration of MDACC 468 cells into the MDACC 435
population.
FIG. 4 Microphotographs obtained for 100% MDACC 435 (top left),
99.9% MDACC 435+0.1% MDACC 468 (top right), and 100% MDACC 468
(bottom left). Box and whisker plots of the population of outliers
show discrimination with statistical significance between the 100%
MDACC 435, and the 99.9% MDACC 435+0.1% MDACC 468 populations.
Moreover, the sensitivity of this technique can be seen as we
identify and plot the characteristics of the outlier cells for the
100% MDACC 435, and 99.9% MDACC 435+0.1% MDACC 468 populations.
FIG. 5. 1. Cells are collected from a lesion using a brush. 2.
Cells are introduced in buffer by snapping head of brush and
dropping it into the tube. 3. Cells are introduced into the
biochip. 4. A reagent cocktail (if not in dried form inside the
biochip) is introduced into the biochip to stain the cells.
FIG. 6. Cells collected are captured on the membrane surface and
labeled by reagents. The cells are identified based on staining of
the nucleus with a nuclear dye (in blue channel-solid color), and
staining of the cytoplasm with an actin filament stain (in red
channel-hatched lines). An antibody to a specific biomarker present
either on the surface or in the interior of the cell is labeled in
the green channel (dotted).
FIG. 7. Schematic showing image processing. For each image, an X-Y
scan of the membrane area (variable area), collecting (n.times.m)
non overlapping images at p different focal planes, is acquired.
Currently n=m=5, p=3 for 5.times.5 XY scan with 3 Z-focal planes.
Each dataset comprised all acquired images is subjected to a
one-push of a button automated routine that does:
Z merging of p focal planes for each location
QA/QC on Z merging (replaces Z-merged if faulty with appropriate
single Z image) or discards if no appropriate image found.
Cell recognition through contouring, dynamic thresholding, masks,
intensity and size filters, segmentation algorithms for the
resulting images. Removal of debris, background subtraction,
identification of cells with no cytoplasm stain, i.e. "lone nuclei"
to be tagged for later possible discrimination. The process
concludes with collection of X parameters in each of the 3 color
channels for each pair of cell cytoplasm and corresponding nucleus
defined from analysis as area of interest for cytoplasm (AOI cyto),
and area of interest for nucleus (AOI nucleus)
FIG. 8. Schematic showing detailed image processing. The process is
detailed here with the first step of Z-merging, followed by QA/QC
on the merged images. Cell recognition is achieved through a series
of image treatments and algorithms that first identify the cells
cytoplasm boundaries, and resolve the potential overlap between the
cells. When too many cells are present, overlapped cells that
cannot be resolved are discarded. Legitimate cells will be cells of
a given size range, and which have only one nucleus. From these
images, areas of interest (AOI) for both the nucleus and the cell
cytoplasm are recorded. Each of these AOIs is then interrogated for
the list of parameters listed above in each of the three colors.
Additional parameters can consist of status (1 or 0) or certain
cells based on parameters cut-off values. This allows for after the
fact filtering of the data according to certain criteria. Final
values for all parameters are then fit into a logistic regression
type equation that weighs each factor in order to produce a score
corresponding to oral cancer risk: OSCC
score=a.sub.0+a.sub.1.times.P.sub.1+a.sub.2.times.P.sub.2+ . . .
+a.sub.n.times.P.sub.n
where a.sub.1.fwdarw.n are weighing coefficients, and
P.sub.1.fwdarw.n are parameters (logged or not) related to
morphology or molecular expression. This score can be normalized to
a value between 0 and 1 corresponding to the malignant progression
between normal (0) and oral cancer (1) through the dysplastic
changes according to the scale shown.
FIG. 9. Preliminary data is shown with the intensity of the surface
biomarker EMMPRIN (CD147) exhibiting the ability to distinguish
between non-neoplastic categories (normal and benign), dysplastic,
and oral cancer.
DETAILED DESCRIPTION OF THE INVENTION
This invention describes an expanded panel of biomarkers to cover
early detection and progression of oral cancer. We analyze cellular
samples obtained from a minimally invasive brush biopsy sample,
simultaneously quantifying cell morphometric data and expression of
molecular biomarkers including at least 2, 3 4, 5, 6 or all of
AVB6, EGFR, Ki67, Geminin, MCM2, Beta Catenin, and EMPPRIN. The
programmable bio-nano-chip approach will be compared to the current
standard of care based on biopsy and histopathological assessment
of the lesions to validate the new method.
The analysis will be performed using a hand held device with
disposable chip that provides a rapid, cost effective, yet
sensitive method of detecting these tumor markers. Additionally,
because of its portability, low cost, and speed, this approach can
function in point of care settings using noninvasive brush biopsy
samples. The invention therefore also includes the disposable chip
with reagents placed thereon that are specific for measuring the
above markers. The device contains power, detection of signal,
programming, and capacity to display the final results.
Brush biopsies from two-thirds of the subjects are being used in
the development of the programmable bio-nano-chip system and
samples from the remaining one-third of subjects will be used in
clinical validation of the PNBC system. The primary outcome for the
study is to confirm the diagnostic sensitivity and specificity of
the PNBC system in distinguishing between non-neoplastic,
dysplastic, and malignant lesions when compared against the gold
standard results provided by scalpel biopsies and histopathological
assessments.
This novel programmable bio-nano-chip approach has the potential to
turn around biopsy results in a matter of minutes as compared to
days for traditional pathology methods. To finalize this model, a
total of 950 patients who present for the scalpel biopsy of a
suspicious oral lesion are being recruited at three clinical sites.
A second clinical trial is also underway to test this model in a
population recruited at primary care settings, which better
represents the prevalence of the disease in the general population.
For these trials, two brush biopsies will be performed--one on the
oral lesion and another on normal appearing mucosa.
Example 1
Proof of Principle
Using some of the same concepts borrowed from our HIV immune
function test, we adapted the flow cell for use with brush biopsy
samples to explore the cytomorphometric features and biomarker
signatures for their capacity to distinguish between oral cancer
and benign lesions. The PNBC sensor system for assessing OSCC
integrates multiple laboratory processes onto a microfluidic
platform in three primary steps: 1) cell separation/capture on the
membrane filter, 2) biomarker immunolabeling and cytochemical
staining, and 3) fluorescent imaging and analysis. No human
intervention is needed once the sample is applied to the device,
until the results are obtained, and the method is fully
automated.
During cell capture, an oral cytology suspension is delivered to
the PNBC sensor, using pressure-driven flow, whereupon any
particles or cells larger than the membrane pore size are retained
on the micro-membrane surface. Once captured, the cells are
serially fluorescently stained in a very rapid process.
The cells are then detected using fluorescence microscopy in an X,
Y, Z scan of the membrane surface. Monochrome images of Phalloidin,
epidermal growth factor receptor (EGFR), and DAPI fluorescent
labels are collected sequentially using appropriate filter cubes,
then merged into red, green, and blue spectral channels,
respectively. Multiple Z-focal planes are collected at +5 .mu.m
intervals and recombined using an automated z-stack focusing
algorithm in ImageJ in order to accommodate adherent epithelial
cell populations with both individual and aggregated cell
clusters.
Automated image analysis routines utilize ImageJ and/or Cell
Profiler open-source software with custom written macros for
quantitative intensity standardization and cell/nuclear contouring
to define the region-of-interest (ROI) for each object/cell. The
cytoplasm is stained fluorescent red with phalloidin (red), the
nucleus blue with DAPI, and any cancer biomarker (e.g. EGFR)
immunofluorescently stained green with FITC labeled monoclonal
antibody.
TABLE-US-00002 TABLE 1 Assay reagents applied in the BNC assays for
oral cancer. WORKING SUPPLIER AND STOCK CONCENTRATION BIOMARKERS
PRODUCT # CONCENTRATION (IN PBSAT) EGFR AB-10 THERMO SCIENTIFIC -
200 .mu.G/ML IN PBS 10 .mu.G/ML (MOUSE MAB - LABVISION #MS- CLONE
111.6) 378-P CLONE: 111.6 ANTI-HUMAN R AND D SYSTEMS 100 .mu.G
(DILUTED IN 10 .mu.G/ML EMMPRIN CATALOG# AF972 0.5 ML PBS FOR 200
.mu.G/ML CONCENTRATION) AVB6 MILLIPORE SIZE: 100 .mu.G 50 .mu.G/ML
CATALOG# CONCENTRATION: MAB2074Z 1 .mu.G/ML CLONE: E7P6 KI67 DAKO
SIZE: 200 .mu.L 1:25 CATALOG# M7240 CLONE: MIB-1 GEMININ ABCAM
SIZE: 100 .mu.l 10 .mu.G/ML CATALOG# AB12147 CONCENTRATION: 0.5
MG/ML MCM2/BM28 BD TRANSDUCTION SIZE: 150 .mu.G 10 .mu.G/ML LABS
CONCENTRATION: CATALOG# 610701 250 .mu.G/ML CLONE: 46/BM28
B-CATENIN BD TRANSDUCTION SIZE: 150 .mu.G 10 .mu.G/ML LABS
CONCENTRATION: CATALOG# 610154 250 .mu.G/ML CLONE: 14
Subsequent automated image analysis routines (see FIGS. 7 and 8)
employ digital filtering and image segmentation of the DAPI and
Phalloidin signals, blue and red spectral channels, respectively,
to generate binary masks and contours of the nuclear and
cytoplasmic ROIs for measurement in all fluorescent channels. This
fully automated programmable bio-nano-chip methodology permits
concurrent analysis of EGFR surface biomarker expression and
cellular/nuclear morphology using over 50 ROI intensity and shape
parameters with particular attention focused on the cellular and
nuclear area, the nuclear/cytoplasmic (N/C) ratio, and mean
cellular EGFR intensity as early indicators of malignancy.
A total of 52 oral brush cytology specimens from healthy and
disease participants were collected from the University of Texas
(UT) Health Science Center at San Antonio, Utah Dental Branch at
Houston, and UT at Austin. Each individual parameter was evaluated
by a receiver operating characteristics (ROC) curve. Reagents were
as in Table 1.
All parameters tested exhibit significant capacity for disease
classification and discrimination between patients with OSCC or
dysplasia versus healthy controls or benign conditions, as
demonstrated by the area under the curve (AUC) values greater than
0.5. The ROC curve generated from the predicted values obtained
from logistic regression models in the combined biomarker panel
exhibited an AUC value of 0.94 with a projected 97% sensitivity and
93% specificity for detection and classification of malignant and
pre-malignant oral lesions.
These promising proof of principle data demonstrate the efficacy of
brush biopsy and programmable bio-nano-chip analysis to distinguish
oral cancer from normal oral mucosa. This expansion addresses the
more significant clinical problem of distinguishing between normal
oral mucosa, dysplastic lesions, non-dysplastic lesions, and
malignant lesions. To maximize the sensitivity and specificity of
PROGRAMMABLE BIO-NANO-CHIP, particularly for pre-malignant lesions,
a broader panel of tumor and dysplasia markers alongside cell
morphometric analysis is implemented.
Example 2
Additional Markers
According to the Oral Cancer Foundation, HPV is now the leading
cause of oral cancers in the US. Indeed, while tobacco continues to
be an important risk factor, an increasing number of never-smoker
patients have been diagnosed with oral cancer, developed by HPV16
infection. The system demonstrated here allows for future
implementation of additional markers already discovered, emerging,
or that will be discovered, that could specify HPV-related oral
cancers.
The Speight and Thornhill team's long track record of research into
the mechanisms associated with the malignant conversion of oral
keratinocytes has enabled identification of specific markers of
malignant conversion. Integrins are a family of molecules that are
important in cell-cell and cell-matrix interactions for which the
importance of cell surface integrin expression, particularly the
expression of .alpha..sub.v.beta..sub.6 by oral keratinocytes, in
the development of a malignant phenotype and invasion of the
connective tissue has been demonstrated. Indeed, it has been shown
that .alpha..sub.v.beta..sub.6 expression correlates with the
degree of dysplasia in lesions and is greatest in those lesions
that progress and in invasive oral cancers.
In normal eukaryotic cells, chromosomal replication is tightly
regulated and coupled to progression through cell cycle.
Minichromosome maintenance (MCM) proteins are present in all phases
of cell cycle, but are absent in quiescent, terminally
differentiated, and senescent "out-of-cycle" states. The MCM
proteins, therefore, represent a new class of proliferation marker.
It has been shown recently that MCM proteins are dysregulated in a
wide range of pre-neoplastic and neoplastic states, representing
powerful tumor markers in a range of organ systems including
cervix, esophagus, bladder, prostate, and brain. The Sheffield team
has shown that MCM proteins MCM2 and geminin, and more traditional
cell proliferation marker Ki67, are over expressed in salivary
tumors and oral cancers, and perhaps more importantly that levels
of these markers were elevated in dysplastic lesions with values
that distinguished them from both NOM and OSCC. A similar situation
has been noted for pre-malignant genito-urinary lesions with
elevated levels of Mcm5 being highly predictive for development of
genito-urinary tract cancer. Preliminary data shows MCM5 may play a
similar role in oral lesions.
Further, animal models developed by Vigneswaran showed that
expression of biomarker EMMPRIN gradually increases during
tumorigenesis, closely simulating its expression pattern in human
HNSCC tumorigenesis. The Wnt-.beta.-catenin pathway is frequently
deregulated in oral cancer, which is identified by nuclear
localization of .beta.-catenin. Importantly, addition of integrins
and MCM proteins along with other tumor markers, such as EGFR,
CD147, .beta.-catenin, and cell proliferation marker Ki67, could
significantly enhance sensitivity and specificity of brush biopsy
analysis for both oral cancer and pre-cancer.
Example 3
Applications
The innovative aspect to the validation of multiple biomarkers
(separately or in a multiplex manner) for differentiating
potentially malignant lesions is the application of a
minimally-invasive brush biopsy test that can be performed in
clinics or dentist's offices. Results will be available in a matter
of minutes, versus hours to days for scalpel biopsies or OraScan
analyses of brush biopsy samples.
The new device is intended to serve as a diagnostic device and not
simply a screening aid for patients that have potentially malignant
lesions (PMLs). In this context the new device is meant to replace
(or augment) the current scalpel biopsy and pathology exam that now
takes more than three days to complete.
Unlike the highly invasive scalpel biopsy, the new bio-nano-chip
device will collect samples with a noninvasive, soft cytology brush
and in doing so will be compatible with sampling of multiple
areas.
These new devices have potential for broad usage in a number of
settings where the diagnosis of intra oral soft tissue is necessary
with particular emphasis on PMLs. Three settings are identified for
the new device as follows:
The primary care setting would involve general dental practices or
primary care medical practices. Most patients with suspicious
lesions causing symptoms will first present to a primary care
clinician or a symptomless lesion may be fortuitously identified in
primary care as a result of a routine dental or medical
examination. These lesions currently pose a diagnostic dilemma for
the primary care clinician i.e. should the lesion be managed in
primary care, observed, referred to a specialist as a routine
referral or referred as an urgent priority?
Since an incisional biopsy is currently the only test with
sufficient diagnostic sensitivity and specificity to distinguish
between these categories, many more patients are referred for
urgent specialist attention than is necessary. This is because i)
most primary care clinicians do not have the expertise to perform
the biopsy, ii) the time it would take, and iii) the biopsy is
better performed by the specialist if they are to be involved in
the further treatment of the patient.
The new technology will enable the primary care clinician to obtain
quantitative diagnostic information about the lesion, whilst the
patient is still in their office, and help direct their decision
about how to manage the patient. It will ensure far fewer
unnecessary specialist referrals and for those patients that do
require specialist referral it will be possible to decide the
degree of urgency of referral and to provide the specialist with
quantitative data to support this decision. For patients that the
primary care clinician elects to manage or observe themselves, they
will be able to make this decision with a far higher degree of
certainty and the option to re-test using the technology at any
time.
Most specialists in secondary care would perform a biopsy on a
suspicious lesion for definitive diagnostic purposes. However,
suspicious lesions are often large or multiple and identifying the
`best` site to biopsy can be challenging. There is always the
concern that a malignancy has been missed because the area biopsied
was not the `right` site. Thus, it is likely that the technology
would be used slightly differently in secondary care than in
primary care. Here it is probably that large or multiple lesions
regarded as highly suspicious would be subjected to brush biopsy
and point of care lab-on-a-chip diagnosis in order to identify the
best site to subject to an incisional biopsy. It is also likely
that many lesions that clinically appear benign would be subjected
to the new technology to provide some quantitative confirmation of
the subjective clinical appearance. Many lesions that are not
malignant, but following an incisional biopsy are found to be
dysplastic, and have the potential to progress to malignancy, are
carefully monitored in secondary care. Regular repeat incisional
biopsy of such lesions to monitor if the lesion is getting better
or worse or to see if it is responding to treatment is difficult,
costly and very unpleasant for the patient. The new technology,
however, would make it far more practical to monitor such lesions
on a regular basis.
Patients diagnosed with oral cancer would normally be referred to
tertiary care surgeon or multidisciplinary team including
oncologists, surgeons etc. for definitive treatment of their cancer
and monitoring for recurrence. In this setting the technology may
be used to multiply sample lesions prior to surgery in order to map
out surgical margins and post surgery to monitor patients for any
recurrence.
Resource poor settings often lack the more advanced secondary and
tertiary referral centers, pathology services etc. that would
complete the full diagnosis of suspicious oral lesions in developed
countries like the US. The new technology is robust and portable
making it ideal for use in the field and other resource poor
settings. In such settings, the ability to diagnose lesions with a
high degree of certainty, within a few minutes and at the point of
contact with the patient, would enable healthcare to quickly
identify patients on whom scarce healthcare resources should be
focused.
Assays for EGFR, as well as proof of concept for new biomarkers
.alpha.v.beta.6, CD147 and Ki67 are shown below in FIG. 2, as
imaged on the programmable bio-nano-chip. For each of these assays,
cells were captured on the surface of the membrane, subjected to a
cocktail of a primary antibody to the biomarker in PBSA and Tween
20, and then to a secondary antibody cocktail consisting of an
AlexaFluor-488 (green) conjugated antibody, as well as DAPI and
Phalloidin for morphometry. The green spectral channel is shown in
the inset for the DOK cell line in the presence of irrelevant
antibody, EGFR, .alpha.v.beta.6, and CD147, showing adequate
staining of the cells in this system. The Ki67 biomarker assay was
developed with the FADU cell line (bottom row), which shows great
nuclear staining in the green channel (bottom right).
Additional features of this approach enable detection of rarer cell
events. We have mixed different ratios of two cancer cell lines,
MDACC 435, expressing with very low (5%) expression of EGFR and
MDACC 468 cells with very high expression of EGFR.
The graphs in FIG. 3 show that as the concentration of the MDACC
468 increase in the mixture of MDACC 435/MDACC 468 from 0, 0.1,
0.5, 1, 10, 25, 50, 75, 90 to 100%, there are noticeable changes in
the average intensity per cell with a sharp increase of cells above
the mean intensity of EGFR for MDACC 435 cells. This change can
also be seen when monitoring the nuclear area as a function of
increasing concentration in MDACC 468 cancerous cells.
Shown in FIG. 4 are one of the 25-scan microphotographs of the 100%
MDACC 435 cells (top left), with the 99.9% MDACC 435+0.1% MDACC 468
(top right). The 100% MDACC 468 cells are shown in the bottom left
panel. A Box and whisker plot of the population of outliers from
these 3 populations (cells with intensity greater than 2 times the
standard deviation of the mean intensity for EGFR in the 100% MDACC
435 cell population) is shown on the bottom right panel,
demonstrating the ability of this approach to discriminate between
two cell lines with high statistical significance, even when the
frequency of one cell line is only about 1 in one thousand. This
proof of concept indicates that the sensitivity, already helpful to
detect important classes of rare cells, might be pushed down lower.
Further dilutions of one cell population into another will be
investigated as well as the addition of one extra step of rare cell
concentration using magnetic beads and or microfluidic
concepts.
The test is run per FIG. 5, and the image analysis proceed as
described in FIG. 6-8. Preliminary data for one marker EMMPRIN
(CD147) is shown in FIG. 9 (a box and whisker plot that shows a
statistical summary of the data wherein the box represents data in
the 25-75 percentile, and the line in the box is the median, the
lines on each side of the box (hatched line) delineate 10-90% data,
and the rest are outliers). Difference between means were
statistically significant (p<0.0001).
The following references are incorporated by reference in their
entirety. Weigum, S. E.; Floriano, P. N.; Christodoulides, N.;
McDevitt, J. T. Lab on a Chip 2007, 7, 995-1003. Weigum, S. E.;
Floriano, P. N.; Redding, S. W.; Yeh, C. K.; Westbrook, S. D.;
McGuff, H. S.; Lin, A.; Miller, F. R.; Villarreal, F.; Rowan, S.
D.; Vigneswaran, N.; Williams, M. D.; McDevitt, J. T. Cancer
Prevention Research 2010, 3, 518-528. US2008038738 61/413,107,
61/484,492, 61/558,165 WO2007002480, WO2005083423, WO2004009840,
WO2005085796, US2009215072 et seq.
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